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  3. Andrea Marinoni
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Førsteamanuensis / Jordobservasjon Institutt for fysikk og teknologi andrea.marinoni@uit.no +4777645178

Andrea Marinoni

  • Luke Cullen, Andrea Marinoni, Jonathan Cullen :
    Machine learning for gap-filling in greenhouse gas emissions databases
    Journal of Industrial Ecology 2024 DOI
  • Eduard Khachatrian, Wolfgang Fritz Otto Dierking, Saloua Chlaily, Torbjørn Eltoft, Frode Dinessen, Nick Hughes m.fl.:
    SAR and Passive Microwave Fusion Scheme: A Test Case on Sentinel-1/AMSR-2 for Sea Ice Classification
    Geophysical Research Letters 2023 ARKIV / DOI
  • Saloua Chlaily, Debanshu Ratha, Pigi Lozou, Andrea Marinoni :
    On Measures of Uncertainty in Classification
    IEEE Transactions on Signal Processing 2023 ARKIV / DOI
  • Mengxi Liu, Qian Shi, Andrea Marinoni, Da He, Xiaoping Liu, Liangpei Zhang :
    Super-Resolution-Based Change Detection Network with Stacked Attention Module for Images with Different Resolutions
    IEEE Transactions on Geoscience and Remote Sensing 2022 DOI
  • Catherine Cecilia A Taelman, Saloua Chlaily, Eduard Khachatrian, Fons Van Der Sommen, Andrea Marinoni :
    On the Exploitation of Heterophily in Graph-Based Multimodal Remote Sensing Data Analysis
    CEUR Workshop Proceedings 2022 ARKIV / FULLTEKST
  • Debanshu Ratha, Malin Johansson, Andrea Marinoni, Torbjørn Eltoft :
    Performance Analysis of Roll-Invariant PolSAR Parameters from C-band images with Regard to Sea Ice Type Separation
    Electronic proceedings (EUSAR) 2022 ARKIV
  • Salman Khaleghian, Habib Ullah, Einar Broch Johnsen, Anders Andersen, Andrea Marinoni :
    AFSD: Adaptive Feature Space Distillation for Distributed Deep Learning
    IEEE Access 2022 ARKIV / DOI
  • Debanshu Ratha, Andrea Marinoni, Torbjørn Eltoft :
    A Generalized Geodesic Distance-Based Approach for Analysis of SAR Observations Across Polarimetric Modes
    IEEE Transactions on Geoscience and Remote Sensing 2022 DOI
  • Salman Khaleghian, Habib Ullah, Thomas Kræmer, Nick Hughes, Torbjørn Eltoft, Andrea Marinoni :
    Sea Ice Classification of SAR Imagery Based on Convolution Neural Networks
    Remote Sensing 2021 ARKIV / DOI
  • Eduard Khachatrian, Saloua Chlaily, Torbjørn Eltoft, Wolfgang Fritz Otto Dierking, Frode Dinessen, Andrea Marinoni :
    Automatic Selection of Relevant Attributes for Multi-Sensor Remote Sensing Analysis: A Case Study on Sea Ice Classification
    IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2021 ARKIV / DOI
  • Saloua Chlaily, Thomas Kræmer, Torbjørn Eltoft, Andrea Marinoni :
    A wavelet-based thermal noise removal approach for Sentinel-1 records on polar areas
    Electronic proceedings (EUSAR) 2021 FULLTEKST
  • Saloua Chlaily, Dino Ienco, Christian Jutten, Andrea Marinoni :
    On Enhanced Ensemble Learning for Multimodal Remote Sensing Data Analysis by Capacity Optimization
    IEEE Statistical Signal Processing Workshop (SSP) 2021 DOI
  • Eduard Khachatrian, Saloua Chlaily, Torbjørn Eltoft, Andrea Marinoni :
    A Multimodal Feature Selection Method for Remote Sensing Data Analysis Based on Double Graph Laplacian Diagonalization
    IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2021 ARKIV / DOI
  • Salman Khaleghian, Habib Ullah, Thomas Kræmer, Torbjørn Eltoft, Andrea Marinoni :
    Deep Semisupervised Teacher–Student Model Based on Label Propagation for Sea Ice Classification
    IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2021 ARKIV / FULLTEKST / DOI
  • Haonan Guo, Qian Shi, Andrea Marinoni, Bo Du, Liangpei Zhang :
    Deep building footprint update network: A semi-supervised method for updating existing building footprint from bi-temporal remote sensing images
    Remote Sensing of Environment 2021 DOI
  • Eduard Khachatrian, Saloua Chlaily, Torbjørn Eltoft, Paolo Gamba, Andrea Marinoni :
    Unsupervised Band Selection for Hyperspectral Datasets by Double Graph Laplacian Diagonalization
    IEEE International Geoscience and Remote Sensing Symposium proceedings 2021 ARKIV / DOI
  • Eduard Khachatrian, Saloua Chlaily, Torbjørn Eltoft, Andrea Marinoni :
    Selecting principal attributes in multimodal remote sensing for sea ice characterization
    VDE Verlag GmbH 2021 ARKIV
  • Desta Haileselassie Hagos, Theofilos Kakantousis, Vladimir Vlassov, Sina Sheikholeslami, Tianze Wang, Jim Dowling m.fl.:
    ExtremeEarth meets satellite data from space
    IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2021 ARKIV / DOI
  • Yao Liu, Lianru Gao, Chenchao Xiao, Ying Qu, Ke Zheng, Andrea Marinoni :
    Hyperspectral image classification based on a shuffled group convolutional neural network with transfer learning
    Remote Sensing 2020 ARKIV / DOI
  • Zhicheng Wang, Lina Zhuang, Lianru Gao, Andrea Marinoni, Bing Zhang, Michael K. Ng :
    Hyperspectral Nonlinear Unmixing by Using Plug-and-Play Prior for Abundance Maps
    Remote Sensing 2020 ARKIV / DOI
  • Sivasakthy Selvakumaran, Cristian Rossi, Andrea Marinoni, Graham Webb, John Bennetts, Elena Barton m.fl.:
    Combined InSAR and Terrestrial Structural Monitoring of Bridges
    IEEE Transactions on Geoscience and Remote Sensing 2020 DOI
  • Fábio M. Bayer, Débora M. Bayer, Andrea Marinoni, Paolo Gamba :
    A Novel Rayleigh Dynamical Model for Remote Sensing Data Interpretation
    IEEE Transactions on Geoscience and Remote Sensing 2020 ARKIV / DOI
  • Saloua Chlaily, Mauro Della Mura, Jocelyn Chanussot, Christian Jutten, Paolo Gamba, Andrea Marinoni :
    Capacity and Limits of Multimodal Remote Sensing: Theoretical Aspects and Automatic Information Theory-Based Image Selection
    IEEE Transactions on Geoscience and Remote Sensing 2020 ARKIV / DOI
  • Debanshu Ratha, Anthony Paul Doulgeris, Andrea Marinoni, Torbjørn Eltoft :
    On Importance of Off-Diagonal Elements in the Polarimetric Covariance Matrix: A Sea Ice Application Perspective
    2023 ARKIV
  • Andrea Marinoni :
    Multimodal data analysis for climate transformation
    2023
  • Luke Cullen, Andrea Marinoni, Jonathan Cullen :
    Machine learning for gap-filling in greenhouse gas emissions databases
    2023
  • Iain Rolland, Sivasakthy Selvakumaran, Andrea Marinoni :
    Remote Sensing Image Completion Using a Diffusion-Based Propagation Algorithm
    2023
  • Andrea Marinoni :
    Satellite imaging can provide more climate-friendly actions
    2023 FULLTEKST
  • Andrea Marinoni, Quitterie Chambon, Antonio Plaza, Stanley Rottman, Michal Shimoni, Richard Hall :
    On the robustness and reliability of target detection in remote sensing
    2023
  • Andrea Marinoni :
    An Expedition to the Arctic in Preparation for Climate Change
    14. april 2023 FULLTEKST
  • Andrea Marinoni :
    Super-spectral-spatial-temporal resolution of environmental data with AI
    2023
  • Andrea Marinoni :
    Multimodal data analysis with sparse and missing data: from fluid graph to soft manifolds
    2023
  • Andrea Marinoni :
    Multimodal data analysis for climate transformation
    2023
  • Andrea Marinoni :
    Satellittfoto kan bidra til meir klima­vennlege løysingar
    2023 FULLTEKST
  • Andrea Marinoni :
    Multimodal remote sensing data analysis: challenges and opportunities
    2023
  • Andrea Marinoni :
    AI for climate transformation
    2023
  • Andrea Marinoni :
    Multimodal data analysis for climate transformation
    2023
  • Andrea Marinoni, Marine Nelly Louise Mercier, Qian Shi, Sivasakthy Selvakumaran, Mark Andrew Girolami :
    Incorporating reliability in graph information propagation by fluid dynamics diffusion: a case of multimodal semisupervised deep learning
    2023
  • Ines Meraoumia, Debanshu Ratha, Emanuele Dalsasso, Loic Denis, Florence Tupin, Andrea Marinoni :
    DESPECKLING OF DUAL-POL GRD SENTINEL-1 IMAGES IN EXTRA-WIDE MODE BY DEEP LEARNING
    2023
  • Catherine Cecilia A Taelman, Johannes Lohse, Eduard Khachatrian, Sam Cremers, Andrea Marinoni :
    Semi-automated classification of sea ice types using C- and L-band SAR data
    2022
  • Debanshu Ratha, Malin Johansson, Andrea Marinoni, Torbjørn Eltoft :
    GD-derived Polarimetric Parameters for identifying Sea Ice in C-band SAR Images
    2022
  • Andrea Marinoni :
    Multimodal AI for climate change adaptation and mitigation
    2022
  • Andrea Marinoni :
    How Satellites Can Help Local Communities Fight Climate Change
    2022 FULLTEKST
  • Salman Khaleghian, Thomas Kræmer, Alistair Everett, Åshild Kiærbech, Nick Hughes, Torbjørn Eltoft m.fl.:
    Synthetic aperture radar data analysis by deep learning for automatic sea ice classification
    2021
  • Debanshu Ratha, Torbjørn Eltoft, Andrea Marinoni :
    Discrimination of Ice and Water using PolSAR Parameter-based Clustering
    2021
  • Salman Khaleghian, Habib Ullah, Thomas Kræmer, Torbjørn Eltoft, Andrea Marinoni :
    A deep semi-supervised learning method based on transductive label propagation for sea/ice classification
    2021
  • Catherine Cecilia A Taelman, Saloua Chlaily, Eduard Khachatrian, Andrea Marinoni :
    Graph-based label propagation for multimodal remote sensing data
    2021
  • Catherine Cecilia A Taelman, Saloua Chlaily, Eduard Khachatrian, Andrea Marinoni :
    On the exploitation of heterophily in graph-based multimodal remote sensing data analysis
    2021
  • Catherine Cecilia A Taelman, Saloua Chlaily, Eduard Khachatrian, Andrea Marinoni :
    On the exploitation of heterophily in graph-based multimodal remote sensing data analysis
    2021
  • Salman Khaleghian, Thomas Kræmer, Alistair Everett, Åshild Kiærbech, Nick Hughes, Torbjørn Eltoft m.fl.:
    Deep learning for enhanced sea ice understanding
    2020

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